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A unique hybrid particle swarm optimisation algorithm for simulation and improvement of crew scheduling problem

Author

Listed:
  • Ali Azadeh
  • Ghazal Asadipour
  • Hesam Eivazy
  • Salman Nazari-Shirkouhi

Abstract

The crew scheduling problem is a set covering or set partitioning problem. It schedules the crew members so that all flights are covered, while the cost is minimised. The crew scheduling is an non-deterministic polynomial-time hard constrained combinatorial optimisation problem, so it cannot be exactly solved in a reasonable computation time. This paper presents a particle swarm optimisation (PSO) algorithm for simulating and solving the crew scheduling problem. The proposed algorithm is extended from the discrete version of PSO. By applying PSO to the crew scheduling problem, the cost is improved when compared with other well-known algorithms. This is the first study that introduces PSO for simulation and optimisation of the crew scheduling problem.

Suggested Citation

  • Ali Azadeh & Ghazal Asadipour & Hesam Eivazy & Salman Nazari-Shirkouhi, 2012. "A unique hybrid particle swarm optimisation algorithm for simulation and improvement of crew scheduling problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 13(4), pages 406-422.
    • Handle: RePEc:ids:ijores:v:13:y:2012:i:4:p:406-422
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    Cited by:

    1. Okan Örsan Özener & Melda Örmeci Matoğlu & Güneş Erdoğan & Mohamed Haouari & Hasan Sözer, 2017. "Solving a large-scale integrated fleet assignment and crew pairing problem," Annals of Operations Research, Springer, vol. 253(1), pages 477-500, June.
    2. Mohamed Haouari & Farah Zeghal Mansour & Hanif D. Sherali, 2019. "A New Compact Formulation for the Daily Crew Pairing Problem," Transportation Science, INFORMS, vol. 53(3), pages 811-828, May.

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